Learning Algorithmic Folk Remedies: Censorship and Critical Media Literacy on Queer TikTok

• In Event: AERA Roundtable Session Saturday 3:20 pm Four Seasons Ballroom 2-3
  In Roundtable Session: Community Connection Across Digital Social Spaces (Table 1)

Abstract

This paper explores how LGBTQ+ TikTok content creators learn to navigate and resist discriminatory content moderation on the platform through innovative media literacy practices. By examining the phenomenon of “algorithmic folk remedies,” the study highlights how queer users develop and share informal, iterative strategies to evade censorship and assert their identities. Utilizing a case study approach, the paper links theories of algorithmic imaginaries with folk knowledge to analyze TikTok’s cisheteronormative content moderation biases. Findings reveal that LGBTQ+ creators engage in tactics such as A/B testing, 'algospeak,' and cross-platform strategies to bypass restrictions. The paper underscores the broader implications for marginalized groups’ resistance against biased digital governance, offering insights into adaptive digital literacy practices.

Author

• Alexander Monea, George Mason University